面向人机交接的模型预测轨迹规划
Model Predictive Trajectory Planning for Human-Robot Handovers
AI总结：
本研究提出一种基于路径跟踪模型预测控制的人机交接轨迹规划方法，结合高斯过程回归预测交接位置以自适应调整路径偏差边界，经7自由度协作机械臂实验验证了其有效性与通用性。
摘要：
本研究提出了一种新型人机交接轨迹规划器。交接需求可通过基于路径跟踪的模型预测控制器自然处理，其中路径进度用作交接的进度衡量指标。此外，路径偏差被用于跟随人体运动，通过交接位置预测自适应调整路径偏差边界。该预测采用在已知交接轨迹上训练的高斯过程回归模型实现。在一台7自由度协作机械臂上开展的实验验证了所提方法的有效性与通用性。
英文摘要：
This work develops a novel trajectory planner for human-robot handovers. The handover requirements can naturally be handled by a path-following-based model predictive controller, where the path progress serves as a progress measure of the handover. Moreover, the deviations from the path are used to follow human motion by adapting the path deviation bounds with a handover location prediction. A Gaussian process regression model, which is trained on known handover trajectories, is employed for this prediction. Experiments with a collaborative 7-DoF robotic manipulator show the effectiveness and versatility of the proposed approach.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
